MedErrBench (English) - Error Detection: leaderboard
Metric: Detection accuracy (%): whether the note contains an error (binary); 208 English test notes adapted from MedQA cases (104 with an error, 104 without) with clinician-verified inserted errors; main-table prompting (the paper does not state its shot setting); printed as fractions and shown times 100; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 14 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Doubao-1.5-Thinking-Pro | 77.9 | #133 |
| 2 | GPT-4o Mini | 66.4 | #588 |
| 3 | GPT-4o | 59.6 | #333 |
| 4 | Llama 3.3 70B Instruct | 58.2 | #520 |
| 5 | Gemini 2.5 Flash Lite | 56.7 | #413 |
| 6 | Qwen 2.5 7B Instruct | 56.3 | #846 |
| 7 | Llama 3.1 8B Instruct | 51.9 | #1018 |
| 8 | Gemini 2.0 Flash | 51.4 | #331 |
| 9 | MedGemma-4B | 50.5 | #731 |
No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.
Interactive version: theaggregate.ai/benchmark?slug=mederrbench-english-error-detection · How It Works · Data refreshed daily, snapshot 2026-10-11.